Mathew Mervin Psy 202 Exam #1 Study Guide
Mathew Mervin Psy 202 Exam #1 Study Guide Psy 202
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This 5 page Study Guide was uploaded by Zoe Notetaker on Monday September 12, 2016. The Study Guide belongs to Psy 202 at University of Mississippi taught by Dr. Mervin Matthew in Fall 2016. Since its upload, it has received 40 views. For similar materials see Elementary Statistics in Psychology (PSYC) at University of Mississippi.
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Date Created: 09/12/16
Exam 1 Psy 202 Study Guide Vocabulary Words: Qualitative Research Uses summaries, unstructured, draws conclusions; in short, quality information and deeper thinking Quantitative Research Uses structured data, statistics, and objective conclusions; in short, it uses numbers Experiments A form or research in which a prediction is tested External Validity Deals with whether or not the same effects that occurred in the lab will be the same in the outside world Random Assignment Test subjects are randomly assigned to control or test groups QuasiExperiment An experiment that cannot use random assignment; the subjects assign themselves Observational Study A study in which subjects are observed and not interfered with by the experimenter Population The entire group of people one is trying to generalize Samples A subset of a population in which one is interested and can test Simple Random Sampling All people in a population have equal chances of being sampled Stratified Sampling divides the population into separate groups, called strata. Then, a probability sample ( often a simple random sample ) is drawn from each group Cluster Sampling Occurs when a population is composed of sub groups and subjects are then taken from each sub group Systematic Sampling Takes every nth person (not everyone has a chance in this method) Deliberate/Purposive Sampling Occurs when one subset is targeted more than another Convenience Sampling People in a sample are those that are easiest to recruit Population Parameters (Uses greek letters) Shows characteristics of a population Sample Statistics (Uses english letters) shows information and characteristics of the sample, not the entire population Independent Variable The one being manipulated by the experimenter Dependent Variable The variable being measured or changed Qualitative Categorical information Quantitative Numerical information and data Discrete No fractional amounts, only whole numbers, not infinite Continuos Has fractional amount, infinitive Construct Using body/ other behavior to infer something Nominal Scales Only gives categorical information Ordinal Scales Gives categorical information, and ranks the categories Interval Scales Gives categorical, rank, and distance information Ratio Scales Category, rank, distance, and uses true zero Reliability Getting the same results repeatedly Validity Measuring what one actually intends to measure Confounds Outside variables that affects the dependent variable Central Tendency The score around which all other scores cluster Variability How spread out the scores are (from the central tendency) Skewness How spread out equal sections of distribution are from each other Kurtosis The highest point on a graph Mode Score that occurs most often in a set of data Median Value that divides the distribution in half (Number in the middle) Mean Average of all scores Range Highest score minus the lowest score Interquartile Range Gets rid of the best and worst scores by using middle quartiles Average Deviation The average of all deviation scores in a set of data Variance A method of calculating deviation from the means of a group Standard Deviation Square root of the variance Degrees of Freedom How many scores are free to do what they want Symmetry Measure of skewness Curvature Measure of kurtosis Box and Whisker Plot A graph in which one or more distributions is broken into quartiles Bar Chart Displays noncontinuous data and deals with categorical scores Pie Charts A circle that is sliced to represents percentages Index of Qualitative Variation A measure of statistical dispersion in nominal distribution Percentile Rank Uses raw scores and convert them into cumulative relative frequency Percentile Converts cumulative relative frequency into raw scores ZTransformation (zscores) the standardized scores Study Guide By Chapter: Chapter 1 Experiments v. quasiexperiments v. observational designs ● An experiment is a form of research that uses random assignment when testing a hypothesis. A quasiexperiment is unable to use random assignment. An observational design prevent the experimenter from interfering with the test subjects. Populations v. samples ● A population is the entire group of people one is trying to generalize, and the sample is the subset of the population in which one is actually testing Look over different types of sampling techniques ● Written above Independent v. dependent ● The independent variable is the one that is being manipulated by the experimenter and the dependent is the variable one is measuring. Qualitative v. quantitative ● Qualitative refers to dealing with categorical information while quantitative uses numbers Continuous v. discrete ● Continuous data uses fractional amounts and is infinite (qualitative) and discrete data only has whole numbers because there is a set number of categories (quantitative) Nominal, ordinal, interval, ratio ● Nominal scales only give a person categorical information, there is no inbetween options or natural order. Ordinal scales give both categorical information and rank the categories. Interval scales give categorical, rank, and distance information. Ratio scale give the most info: categorical, rank, distance, and the true zero. Reliability (in general) ● An experiment is reliable if it is redone and the same results are achieved repeatedly Validity (in general) ● An experiment is valid if one measures what they intend to and not any confounds Chapter 2 Frequency tables ● Simple frequency tables have 2 columns and include all possible values, more columns are added as the frequency type changes and becomes more complex Relative frequency, and cumulative frequency ● Relative frequency is simple frequency divided by the total number of scores; absolute frequency is normalized by total number. Cumulative frequency looks at the scores above or below a distribution Ungrouped v. grouped ● Ungrouped frequencies deal with each score, while grouped frequencies have ranges and intervals that group similar scores together ○ Number of intervals: 1020 ○ Width of intervals: 2,3, or multiples of 5 Histograms, frequency polygons, ogives, and stemandleaf plots ● Histograms deal with both simple and relative frequencies, basic bar graph in which bars must touch; frequencies are on yaxis and raw values are on xaxis ● Frequency Polygons deal with both relative and simple frequencies; interchangeable use with histograms; dots on graph are connected by a line, the line but touch the xaxis twice ● Ogives are graphs designed to show one cumulative frequencies; basically escalating dots that are not connected ● StemandLeaf Plots show the shape of a distribution for individual scores in an interval Chapter 3 Central tendency ● Central tendency is the score around which all other scores cluster Mean v. median v. mode ● Mean is the average of all scores, and it is used when one is being the most accurate ● Median is the value that divides the distribution in half, it includes rank and categorical information only ● Mode is the score that occurs the most, it is only categorical information Range v. interquartile range ● Range is the highest score minus the lowest score of a distribution while the interquartile range is the subtraction of the 2nd quartile to the third Average deviation v. variance and standard deviation ● Average deviation is simply the average of all the deviation scores in a set of data ● Variance is a method of calculating standard deviation from the means of a group ● Standard deviation in the square root of the variance Chapter 4 o Bar charts and pie charts ● Bar charts show noncontinuous data with no skewness or kurtosis; categorical information ● A sliced circle used to show percentages; rf is used more than f o Index of qualitative variation ● A measure of statistical dispersion in nominal distribution Chapter 5 Percentile rank ● The percentile rank uses raw scores and converts them to cumulative relative frequency ● It tells us the Standardized Scores (zscores) and that estimates how far something is from the mean Characteristics of their distribution ● Zscores always have a variance and standard deviation of 1, and a summation and mean of zero Why they’re preferred over percentile ranks ● Sscores allow one to compare two scores from different sets of distributions
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